import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable
def create_scatter(df, dataset_values, ax, cmap="RdBu", titlename="name?"):
# Create separate dataframes for each dataset
df_literature = df[df["dataset"] == dataset_values[0]]
df_new = df[df["dataset"] == dataset_values[1]]
# Create the scatter plots
scatters = []
for df, alpha in zip([df_literature, df_new], [0.2, 0.9]):
scatter = ax.scatter(df["UMAP Component 1"], df["UMAP Component 2"], c=df["p value"], cmap=cmap, edgecolor="grey",
s=500, marker='.', alpha=alpha, vmin=0, vmax=0.1)
scatters.append(scatter)
ax.set_xlabel("UMAP Component 1", fontsize=20)
ax.set_ylabel("UMAP Component 2", fontsize=20)
ax.tick_params(axis='both', which='major', labelsize=20)
# set the subplot title to the dataset name
ax.set_title(titlename, fontsize=20, y=1.05)
# make equal aspect ratio
ax.set_aspect('equal', 'box')
return scatters
# create the subplots of 2x2
fig, ax = plt.subplots(2, 2, figsize=(18, 15), dpi=150)
datasets = [(df_C_new_FeCrNiMoTi_Mahl_label, ['corrosion data', 'new NiCrMoTiFe data'], "RdBu", "new FeCrNiMoTi to corrosion dataset"),
(df_C_new_FeCrNiCoV_Mahl_label, [
'corrosion data', 'new NiCrCoVFe data'], "RdBu", "new FeCrNiCoV to corrosion dataset"),
(df_H_new_FeCrNiMoTi_Mahl_label, [
'hardness data', 'new NiCrMoTiFe data'], "RdYlBu", "new FeCrNiMoTi to hardness dataset"),
(df_H_new_FeCrNiCoV_Mahl_label, ['hardness data', 'new NiCrCoVFe data'], "RdYlBu", "new FeCrNiCoV to hardness dataset")]
# Get global min and max for UMAP components
xmin, xmax = min(df['UMAP Component 1'].min() for df, _, _, _ in datasets), max(
df['UMAP Component 1'].max() for df, _, _, _ in datasets)
ymin, ymax = min(df['UMAP Component 2'].min() for df, _, _, _ in datasets), max(
df['UMAP Component 2'].max() for df, _, _, _ in datasets)
for i, (df, dataset_values, cmap, title) in enumerate(datasets):
axi = ax[i//2, i % 2] # Get the current axis
scatters = create_scatter(df, dataset_values, axi,
cmap=cmap, titlename=title)
# Set the limits
axi.set_xlim(xmin, xmax)
axi.set_ylim(ymin, ymax)
# Create a divider for the existing axes instance
divider = make_axes_locatable(axi)
# Append axes for colorbar to the right of axi, with 5% width of axi
cax = divider.append_axes("right", size="5%", pad=0.1)
cbar = fig.colorbar(scatters[-1], cax=cax)
cbar.set_label("p-value", size=20, labelpad=10)
cbar.ax.tick_params(labelsize=20)
plt.tight_layout()
plt.savefig('UMAP 2D_Mahalanobis.png')
plt.show()
